While enterprises are actively exploring the potential of agentic AI, execution risks remain high. In our experience, the wrong choice of use case is the most common reason these projects fail. 

To avoid costly missteps, organizations must look beyond the hype. Not every business need calls for an AI agent. Use the checklist below to evaluate whether agentic AI is the right fit: 

✅ Is the task complex enough? → If the task is highly structured and rule-based, a traditional workflow or automation script may deliver better results—faster and cheaper. 

✅ Is the task valuable enough? → Routine, low-value activities (like simple data entry) are often better suited to RPA bots than AI agents. 

✅ Are all the steps feasible to automate? → Full automation is ideal, but sometimes it’s smarter to reduce the scope or incorporate human-in-the-loop validation where needed. 

✅ What’s the cost of error? → When mistakes are expensive or hard to catch, start with low-risk, high-recoverability scenarios to build confidence. 

💡 Agentic AI isn't a silver bullet. Applying it to every problem is like wielding a hammer and seeing everything as a nail. Use this checklist to ensure your use case is both technically feasible and commercially justifiable before committing resources. 

Curious to see where agentic AI is already making an impact? Get in touch—we’re happy to share the real-world use cases we've successfully implemented for our clients.

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